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doi: 10.5061/dryad.kc688
To evaluate progress on political biodiversity objectives, biodiversity monitoring provides information on whether intended results are being achieved. Despite scientific proof that monitoring and evaluation increase the (cost) efficiency of policy measures, cost estimates for monitoring schemes are seldom available, hampering their inclusion in policy programme budgets. Empirical data collected from 12 case studies across Europe were used in a power analysis to estimate the number of farms that would need to be sampled per major farm type to detect changes in species richness over time for four taxa (vascular plants, earthworms, spiders and bees). A sampling design was developed to allocate spatially, across Europe, the farms that should be sampled. Cost estimates are provided for nine monitoring scenarios with differing robustness for detecting temporal changes in species numbers. These cost estimates are compared with the Common Agricultural Policy (CAP) budget (2014–2020) to determine the budget allocation required for the proposed farmland biodiversity monitoring. Results show that the bee indicator requires the highest number of farms to be sampled and the vascular plant indicator the lowest. The costs for the nine farmland biodiversity monitoring scenarios corresponded to 0·01%–0·74% of the total CAP budget and to 0·04%–2·48% of the CAP budget specifically allocated to environmental targets. Synthesis and applications. The results of the cost scenarios demonstrate that, based on the taxa and methods used in this study, a Europe-wide farmland biodiversity monitoring scheme would require a modest share of the Common Agricultural Policy budget. The monitoring scenarios are flexible and can be adapted or complemented with alternate data collection options (e.g. at national scale or voluntary efforts), data mobilization, data integration or modelling efforts.
Farmland species richness dataData contains species richness of plants, earthworm, spiders and bees (wild bees and bumblebees) in 195 farms in 12 study regions in Europe. The observed species richness are complemented by a 5% lower and a 95% upper confidence level derived from species accumulation as well as the number of samples drawn in each farm.Geijzendorffer_et_al_2015_farm_species_richness.csv
agri-environment schemes, Empirical data, plants, habitat, power analysis, earth worms, empirical data, species trend, Species trend, common agricultural policy, 2010, Farming system, spiders, farmland biodiversity, Earth worms, Biodiversity indicator, sampling design, farming system, bees, species richness, Common Agricultural Policy, agriculture, biodiversity indicator
agri-environment schemes, Empirical data, plants, habitat, power analysis, earth worms, empirical data, species trend, Species trend, common agricultural policy, 2010, Farming system, spiders, farmland biodiversity, Earth worms, Biodiversity indicator, sampling design, farming system, bees, species richness, Common Agricultural Policy, agriculture, biodiversity indicator
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